Often, stopwords are generated via qualitative, intuitive approaches. Researchers have also employed model-agnostic statistical approaches that generate specific stopword sets for a given corpus of text. One early, naive approach involves ranking all words in a given corpus by frequency and simply omitting the top-\(n\)  most frequent words [1]}. However, more sophisticated approaches have developed over time.
